Wide-Area Image Acquiring Method and Apparatus

ABSTRACT

A wide-area image acquiring method which includes capturing a global image in a preset wide-area visual area, capturing at least two partial images whose definition is preset and that are in the preset wide-area visual area, where the global image covers at least an overlap portion of view ranges of the partial images in the preset wide-area visual area, and a sum of the view ranges of the at least two partial images is greater than or equal to a view range of the global image, determining, in the global image, positions of edges of the partial images, based on same shot objects in the partial images and the global image, and performing splice processing on the at least two partial images according to the positions of the edges, to obtain a composite wide-area image of the wide-area visual area.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of International Patent ApplicationNo. PCT/CN2015/081625, filed on Jun. 17, 2015, which claims priority toChinese Patent Application No. 201410309376.0, filed on Jun. 30, 2014.The disclosures of the aforementioned applications are herebyincorporated by reference in their entireties.

TECHNICAL FIELD

Embodiments of the present disclosure relate to informationtechnologies, and in particular, to a wide-area image acquiring methodand apparatus.

BACKGROUND

Wide-angle images or wide-angle videos provide a new form of organizingspatio-temporal information, provide people with images or videos thatare better than those of conventional common visual angles, bring newviewing experience, and have a wide prospect of application andextensive study values.

In other approaches, partial high-definition images of one largewide-angle visual area are separately obtained using multiplehigh-definition single-lens cameras, and then splice processing isperformed on the captured partial high-definition images. For awide-angle video, partial high-definition pictures of one largewide-angle visual area in each image frame are separately obtained usingmultiple video cameras, and then splice processing is performed on thepartial high-definition pictures in each image frame. However, accordingto this method, a spliced image may have a deviation from an actualimage, and a precision of the obtained image is not high.

SUMMARY

Embodiments of the present disclosure provide a wide-area imageacquiring method and apparatus, to overcome a problem in the otherapproaches that a precision of an acquired image is not high.

A first aspect of the embodiments of the present disclosure provides awide-area image acquiring method, including capturing a global image ina preset wide-area visual area, and capturing at least two partialimages in the preset wide-area visual area, where the global imagecovers at least an overlap portion of view ranges of the partial imagesin the preset wide-area visual area, a sum of the view ranges covered bythe at least two partial images is greater than or equal to a view rangecovered by the global image, and the view range refers to a maximum areacovered by an image visual field, and determining, in the global image,positions that are of edges of the partial images, based on same shotobjects that are in the partial images and also in the global image, andperforming splice processing on the at least two partial imagesaccording to the positions that are of the edges of the partial imagesand that are in the global image, to obtain a composite wide-area imageof the wide-area visual area.

With reference to the first aspect, in a first possible implementationmanner of the first aspect, a resolution of the partial images isgreater than a resolution of the global image, and before determining,in the global image, positions that are of edges of the partial images,based on same shot objects that are in the partial images and also inthe global image, the method further includes adjusting a pixel quantityof the global image such that an adjusted pixel quantity of the sameshot objects in the global image is the same as a pixel quantity of thesame shot objects in the partial images.

With reference to the first possible implementation manner of the firstaspect, in a second possible implementation manner of the first aspect,adjusting a pixel quantity of the global image further includesseparately matching feature points of the at least two partial imageswith features points of the global image, and performing fitting onmatched feature points, and performing interpolation calculation onfitted feature points, to obtain an adjusted global image.

With reference to the second possible implementation manner of the firstaspect, in a third possible implementation manner of the first aspect,performing fitting on matched feature points, and performinginterpolation calculation on fitted feature points, to obtain anadjusted global image includes obtaining an adjustment transformationmatrix by means of fitting according to a position transformationrelationship between the matched feature points in the partial imagesand the matched feature points in the global image, determining,according to the adjustment transformation matrix, positions that are ofall first pixels in the global image and that are in the adjusted globalimage, and filling, with second pixels, positions that are in theadjusted global image and that are other than those of the first pixels,to obtain an adjusted image.

With reference to any one of the first aspect or the first to the thirdpossible implementation manners of the first aspect, in a fourthpossible implementation manner of the first aspect, before determining,in the global image, positions that are of edges of the partial images,based on same shot objects that are in the partial images and also inthe global image, the method further includes separately performingalignment processing between the same shot objects in the at least twopartial images and the same shot objects in the global image, toeliminate a visual difference between the at least two partial images.

With reference to the fourth possible implementation manner of the firstaspect, in a fifth possible implementation manner of the first aspect,separately performing alignment processing between the same shot objectsin the at least two partial images and the same shot objects in theglobal image includes determining the matched feature points that are inthe partial images and that are in the global image, where the matchedfeature points are feature points whose color attributes of pixels arethe same, and initially estimating, according to the matched featurepoints, the same shot objects that are in the partial images and thatare in the global image, revising the initially estimated same shotobjects according to a distance from a matching feature point in the atleast two partial images to a neighboring pixel of the feature point,and a sum of offsets between all matched feature points in the partialimages and all matched feature points in the global image using a Markovrandom field algorithm, where the offset is a sum of a first distanceand a second distance, where the first distance is an offset distancebetween a matched feature point in the partial images and a matchedfeature point in the global image, and the second distance is an offsetdistance between a neighboring pixel of a matched feature point in thepartial images and a neighboring pixel of a matched feature point in theglobal image, and performing deformation processing on the partialimages according to the revised same shot objects that are in thepartial images and that are in the global image such that the same shotobjects in the at least two partial images are separately aligned withthe same shot objects in the global image.

With reference to the fifth possible implementation manner of the firstaspect, in a sixth possible implementation manner of the first aspect,determining the matched feature points that are in the partial imagesand that are in the global image, where the matched feature points arefeature points whose color attributes of pixels are the same, andinitially estimating, according to the matched feature points, the sameshot objects that are in the partial images and that are in the globalimage includes performing the following operations on each first matchedfeature point that is in the partial images and that is in the globalimage using projection coordinates that are of the first feature pointand that are in the partial images as a first estimation point, andacquiring an epipolar line that is of the first estimation point andthat is in the global image, and searching the epipolar line of thefirst estimation point for a second feature point that matches the firstfeature point and that is in the global image, and using a set of thefirst feature point and a set of the second feature point as the sameshot objects that are in the partial images and that are in the globalimage.

With reference to any one of the first aspect or the first to the sixthpossible implementation manners of the first aspect, in a seventhpossible implementation manner of the first aspect, before determining,in the global image, positions that are of edges of the partial images,based on same shot objects that are in the partial images and also inthe global image, the method further includes capturing a firstcalibration image corresponding to the partial images and a secondcalibration image corresponding to the global image, where a visual areaof the first calibration image includes at least one calibration boardthat is on a same plane, and a visual area of the second calibrationimage includes the calibration board in the visual area of the firstcalibration image, enlarging the second calibration image, andperforming distortion correction processing on the second calibrationimage according to a distortion coefficient of the global image, toobtain a first corrected image of the global image, calculating adistortion coefficient of the partial images according to the firstcalibration image and the first corrected image, and performingdistortion correction processing on the partial images according to thedistortion coefficient of the partial images.

With reference to any one of the first aspect or the first to theseventh possible implementation manners of the first aspect, in aneighth possible implementation manner of the first aspect, determining,in the global image, positions that are of edges of the partial images,based on same shot objects that are in the partial images and also inthe global image, and performing splice processing on the at least twopartial images according to the positions that are of the edges of thepartial images and that are in the global image, to obtain a compositewide-area image of the wide-area visual area further includesdetermining, according to color attributes of pixels in the partialimages and color attributes of pixels in the global image, the same shotobjects that are in the partial images and that are in the global image,determining, according to the same shot objects that are in the partialimages and that are in the global image, the positions that are of theedges of the partial images and that are in the global image,determining an overlap area of the at least two partial images accordingto the positions that are of the edges of the partial images and thatare in the global image, where the overlap area is an overlap area ofthe shot objects in the at least two partial images, and determining asplice joint between the at least two partial images according to theoverlap area of the at least two partial images such that an image inthe overlap area of the at least two partial images evenly transits, andperforming splice processing on the at least two partial imagesaccording to the determined splice joint.

With reference to the eighth possible implementation manner of the firstaspect, in a ninth possible implementation manner of the first aspect,before determining a splice joint between the at least two partialimages, the method further includes filling a blackhole area in thepartial images with pixels according to a shot object in the globalimage, where the blackhole area is a shot object that exists in theglobal image but cannot be displayed in the partial images due to mutualblock by objects.

With reference to any one of the first aspect or the first to the ninthpossible implementation manners of the first aspect, in a tenth possibleimplementation manner of the first aspect, view ranges of capturedneighboring partial images partially overlap.

With reference to any one of the first aspect or the first to the tenthpossible implementation manners of the first aspect, in an eleventhpossible implementation manner of the first aspect, the global image isa dynamic image, and the partial images are dynamic images, capturing aglobal image in a preset wide-area visual area, and capturing at leasttwo partial images in the preset wide-area visual area, where the globalimage covers at least an overlap portion of view ranges of the partialimages in the preset wide-area visual area, a sum of the view rangescovered by the at least two partial images is greater than or equal to aview range covered by the global image includes capturing a global imagethat is in each frame and that is in the preset wide-area visual areaand at least two partial images that are in each frame and that are inthe preset wide-area visual area, where for each frame, the global imagein the frame covers at least an overlap portion of view ranges of thepartial images in the frame, and a sum of the view ranges covered by theat least two partial images in the frame is greater than or equal to aview range covered by the global image in the frame, and determining, inthe global image, positions that are of edges of the partial images,based on same shot objects that are in the partial images and also inthe global image, and performing splice processing on the at least twopartial images according to the positions that are of the edges of thepartial images and that are in the global image, to obtain a compositewide-area image of the wide-area visual area includes determining, foreach frame, based on a same shot object that is in each of the partialimages in the frame and that is in the global image in the frame, aposition that is of an edge of each partial image in the frame and thatis in the global image in the frame, and performing splice processing onthe at least two partial images in the frame according to the positionthat is of the edge of each partial image in the frame and that is inthe global image in the frame, to obtain a composite wide-area imagethat is in the frame and that is of the wide-area visual area.

A second aspect of the embodiments of the present disclosure provides awide-area image acquiring apparatus, including a capture moduleconfigured to capture a global image in a preset wide-area visual area,and capture at least two partial images in the preset wide-area visualarea, where the global image covers at least an overlap portion of viewranges of the partial images in the preset wide-area visual area, a sumof the view ranges covered by the at least two partial images is greaterthan or equal to a view range covered by the global image, and the viewrange refers to a maximum area covered by an image visual field, and aprocessing module configured to determine, in the global image,positions that are of edges of the partial images, based on same shotobjects that are in the partial images and also in the global image, andperform splice processing on the at least two partial images accordingto the positions that are of the edges of the partial images and thatare in the global image, to obtain a composite wide-area image whosedefinition is preset.

With reference to the second aspect, in a first possible implementationmanner of the second aspect, a resolution of the partial images isgreater than a resolution of the global image, and the apparatus furtherincludes a global image adjustment module, where the global imageadjustment module is configured to adjust a pixel quantity of the globalimage such that an adjusted pixel quantity of the same shot objects inthe global image is the same as a pixel quantity of the same shotobjects in the partial images before the processing module determines,in the global image, positions that are of edges of the partial images,based on same shot objects that are in the partial images and also inthe global image.

With reference to the first possible implementation manner of the secondaspect, in a second possible implementation manner of the second aspect,the global image adjustment module includes a feature point matchingunit configured to separately perform feature point matching between theat least two partial images and the global image, where the matchedfeature points are feature points whose color attributes of pixels arethe same, a fitting unit configured to perform fitting on the matchedfeature points, and an interpolation calculation unit configured toperform interpolation calculation on fitted feature points, to obtain anadjusted global image, where the adjusted pixel quantity of the sameshot objects in the global image is the same as the pixel quantity ofthe same shot objects in the partial images.

With reference to the second possible implementation manner of thesecond aspect, in a third possible implementation manner of the secondaspect, the fitting unit is further configured to obtain an adjustmenttransformation matrix by means of fitting according to a positiontransformation relationship between the matched feature points in thepartial images and the matched feature points in the global image, anddetermine, according to the adjustment transformation matrix, positionsthat are of all first pixels in the global image and that are in theadjusted global image, and correspondingly, the interpolationcalculation unit is further configured to fill, with second pixels,positions that are in the adjusted global image and that are other thanthose of the first pixels, to obtain an adjusted image.

With reference to any one of the second aspect or the first to the thirdpossible implementation manners of the second aspect, in a fourthpossible implementation manner of the second aspect, the apparatusfurther includes a parallax adjustment module configured to separatelyperform alignment processing between the same shot objects in the atleast two partial images and the same shot objects in the global image,to eliminate a visual difference between the at least two partial imagesbefore the processing module determines, in the global image, positionsthat are of edges of the partial images, based on same shot objects thatare in the partial images and also in the global image.

With reference to the fourth possible implementation manner of thesecond aspect, in a fifth possible implementation manner of the secondaspect, the parallax adjustment module includes a shot object initialestimation unit configured to determine the matched feature points thatare in the partial images and that are in the global image, where thematched feature points are feature points whose color attributes ofpixels are the same, and initially estimate, according to the matchedfeature points, the same shot objects that are in the partial images andthat are in the global image, a revision unit configured to revise theinitially estimated same shot objects according to a distance from amatched feature point in the at least two partial images to aneighboring pixel of the feature point, and a sum of offsets between allmatched feature points in the partial images and all matched featurepoints in the global image using a Markov random field algorithm, wherethe offset is a sum of a first distance and a second distance, where thefirst distance is an offset distance between a matched feature point inthe partial images and a matched feature point in the global image, andthe second distance is an offset distance between a neighboring pixel ofa matched feature point in the partial images and a neighboring pixel ofa matched feature point in the global image, and a shot object alignmentprocessing unit configured to perform deformation processing on thepartial images according to the revised same shot objects that are inthe partial images and that are in the global image such that the sameshot objects in the at least two partial images are separately alignedwith the same shot objects in the global image.

With reference to the fifth possible implementation manner of the secondaspect, in a sixth possible implementation manner of the second aspect,where the parallax adjustment module further includes a same shot objectdetermining unit configured to perform the following operations on eachfirst matched feature point that is in the partial images and that is inthe global image using projection coordinates that are of the firstfeature point and that are in the partial images as a first estimationpoint, and acquiring an epipolar line that is of the first estimationpoint and that is in the global image, searching the epipolar line ofthe first estimation point for a second feature point that matches thefirst feature point and that is in the global image, and using a set ofthe first feature point and a set of the second feature point as thesame shot objects that are in the partial images and that are in theglobal image.

With reference to any one of the second aspect or the first to the sixthpossible implementation manners of the second aspect, in a seventhpossible implementation manner of the second aspect, the parallaxadjustment module further includes a partial image correction unitconfigured to capture a first calibration image corresponding to thepartial images and a second calibration image corresponding to theglobal image before the processing module determines, in the globalimage, positions that are of edges of the partial images, based on sameshot objects that are in the partial images and also in the globalimage, where a visual area of the first calibration image includes atleast one calibration board that is on a same plane, and a visual areaof the second calibration image includes the calibration board in thevisual area of the first calibration image, enlarge the secondcalibration image, and perform distortion correction processing on thesecond calibration image according to a distortion coefficient of theglobal image, to obtain a first corrected image of the global image,calculate a distortion coefficient of the partial images according tothe first calibration image and the first corrected image, and performdistortion correction processing on the partial images according to thedistortion coefficient of the partial images.

With reference to any one of the second aspect or the first to theseventh possible implementation manners of the second aspect, in aneighth possible implementation manner of the second aspect, theprocessing module further includes a same shot object determining unitconfigured to determine, according to color attributes of pixels in thepartial images and color attributes of pixels in the global image, thesame shot objects that are in the partial images and that are in theglobal image, and a splice unit configured to determine, according tothe same shot objects that are in the partial images and that are in theglobal image, the positions that are of the edges of the partial imagesand that are in the global image, determine an overlap area of the atleast two partial images according to the positions that are of theedges of the partial images and that are in the global image, where theoverlap area is an overlap area of the shot objects in the at least twopartial images, and determine a splice joint between the at least twopartial images according to the overlap area of the at least two partialimages such that an image in the overlap area of the at least twopartial images evenly transits, and perform splice processing on the atleast two partial images according to the determined splice joint.

With reference to the eighth possible implementation manner of thesecond aspect, in a ninth possible implementation manner of the secondaspect, the processing module further includes a filling unit configuredto fill a blackhole area in the partial images with pixels according toa shot object in the global image before the processing moduledetermines a splice joint between the at least two partial images, wherethe blackhole area is a shot object that exists in the global image butcannot be displayed in the partial images due to mutual block byobjects.

With reference to any one of the second aspect or the first to the ninthpossible implementation manners of the second aspect, in a tenthpossible implementation manner of the second aspect, view ranges ofneighboring partial images captured by the capture module partiallyoverlap.

By means of a wide-area image acquiring method in the embodiments of thepresent disclosure, a global image in a preset wide-area visual area andat least two partial images in the preset wide-area visual area arecaptured, where the global image covers at least an overlap portion ofview ranges of the partial images in the preset wide-area visual area,and a sum of the view ranges of the at least two partial images isgreater than or equal to a view range of the global image, positionsthat are of edges of the partial images and that are in the global imageare determined based on same shot objects that are in the partial imagesand that are in the global image, and then splice processing isperformed on the at least two partial images according to the positionsthat are of the edges of the partial images and that are in the globalimage, to obtain a composite wide-area image of the wide-area visualarea, which increases a precision of a spliced wide-area image.

BRIEF DESCRIPTION OF DRAWINGS

To describe the technical solutions in the embodiments of the presentdisclosure more clearly, the following briefly introduces theaccompanying drawings required for describing the embodiments. Theaccompanying drawings in the following description show some embodimentsof the present disclosure, and a person of ordinary skill in the art maystill derive other drawings from these accompanying drawings withoutcreative efforts.

FIG. 1 is a flowchart of Embodiment 1 of a wide-area image acquiringmethod according to the present disclosure;

FIG. 2A is a flowchart of another optional implementation manner of thewide-area image acquiring method shown in FIG. 1;

FIG. 2B is a detailed flowchart of step 2027 in the method shown in FIG.2A;

FIG. 3 is a flowchart of still another optional implementation manner ofthe wide-area image acquiring method shown in FIG. 1;

FIG. 4A and FIG. 4B are a flowchart of Embodiment 2 of a wide-area imageacquiring method according to the present disclosure;

FIG. 4C is a flowchart of an optional implementation manner of stepS4033 in the method shown in FIG. 4A and FIG. 4B;

FIG. 4D is a flowchart of another optional implementation manner of stepS4033 in the method shown in FIG. 4A and FIG. 4B;

FIG. 5A is a schematic diagram of data processing of steps S401 and S402in the method shown in FIG. 4A and FIG. 4B to FIG. 4D;

FIG. 5B is a schematic diagram of data processing of step S4031 in themethod shown in FIG. 4A and FIG. 4B to FIG. 4D;

FIG. 5C is a schematic diagram of data processing of step S4032 in themethod shown in FIG. 4A and FIG. 4B to FIG. 4D;

FIG. 5D is a schematic diagram of data processing of step S4033 in themethod shown in FIG. 4A and FIG. 4B to FIG. 4D;

FIG. 5E is a schematic diagram of data processing of steps S4034-11,S4034-12, and S4034-13 in the method shown in FIG. 4A and FIG. 4B toFIG. 4D;

FIG. 5F is a schematic diagram of data processing of step S4038-3 in themethod shown in FIG. 4A and FIG. 4B to FIG. 4D;

FIG. 5G is a schematic diagram of data processing of step S4038-4 in themethod shown in FIG. 4A and FIG. 4B to FIG. 4D;

FIG. 6 is a flowchart of Embodiment 3 of a wide-area image acquiringmethod according to the present disclosure;

FIG. 7 is a schematic diagram of data processing of step S601 in themethod shown in FIG. 6;

FIG. 8A is a schematic structural diagram of Embodiment 1 of a wide-areaimage acquiring apparatus according to the present disclosure;

FIG. 8B is an optional schematic structural diagram of a processingmodule 12 in Embodiment 1 shown in FIG. 8A;

FIG. 8C is another optional schematic structural diagram of theprocessing module 12 in Embodiment 1 shown in FIG. 8A;

FIG. 9A is a schematic structural diagram of Embodiment 2 of a wide-areaimage acquiring apparatus according to the present disclosure;

FIG. 9B is an optional schematic structural diagram of a global imageadjustment module 13 in Embodiment 2 shown in FIG. 9A;

FIG. 10A is a schematic structural diagram of Embodiment 3 of awide-area image acquiring apparatus according to the present disclosure;

FIG. 10B is an optional schematic structural diagram of a parallaxadjustment module 14 in Embodiment 3 shown in FIG. 10A;

FIG. 10C is another optional schematic structural diagram of theparallax adjustment module 14 in Embodiment 3 shown in FIG. 10A; and

FIG. 10D is still another optional schematic structural diagram of theparallax adjustment module 14 in Embodiment 3 shown in FIG. 10A.

DESCRIPTION OF EMBODIMENTS

To make the objectives, technical solutions, and advantages of theembodiments of the present disclosure clearer, the following clearlydescribes the technical solutions in the embodiments of the presentdisclosure with reference to the accompanying drawings in theembodiments of the present disclosure. The described embodiments are apart rather than all of the embodiments of the present disclosure. Allother embodiments obtained by a person of ordinary skill in the artbased on the embodiments of the present disclosure without creativeefforts shall fall within the protection scope of the presentdisclosure.

FIG. 1 is a flowchart of Embodiment 1 of a wide-area image acquiringmethod according to the present disclosure. As shown in FIG. 1, themethod in this embodiment may include the following steps.

Step 101: Capture a global image in a preset wide-area visual area, andcapture at least two partial images in the preset wide-area visual area,where the global image covers at least an overlap portion of view rangesof the partial images in the preset wide-area visual area, a sum of theview ranges covered by the at least two partial images is greater thanor equal to a view range covered by the global image, and the view rangerefers to a maximum area covered by an image visual field.

An image shooting function of a camera may be seen as a process ofemulating a human eye to observe a surrounding environment. In ashooting process, an optical center of the camera, that is, a shootingviewpoint, is equivalent to the human eye, and a size of a wide angle ofthe camera is equivalent to a size of a visual angle of the eye. Avisual area may be a shot area that starts from a viewpoint or a nearviewpoint, where the shot area may be jointly determined by a viewfinderdirection of the camera and the wide angle size and a viewpoint of thecamera. For example, starting from a viewpoint of a camera, on a ray ina shooting direction, there are infinite planes perpendicular to theray, and a size and a position of an area that can be shot and that ison each plane is decided by a wide angle size of a shooting device and adistance from the plane to a shooting point, where the plane isgenerally a rectangle, and then infinite rectangles whose center pointsare located on the ray may be determined by means of the infiniteplanes, where the infinite rectangles may form a pyramid whose apex isthe viewpoint, and the shot object may be shot by the camera when a shotobject enters the pyramid, where the pyramid may be referred to as ashot area, that is, a visual area.

Shooting a shot object that enters a visual area to obtain an image isequivalent to that faces of shot objects are mapped to a plane, wherethe shot objects are in this visual area and are different in shapes ordifferent in distances, and the faces face toward the lens and are notblocked. A view range of an image refers to a maximum area of the facesthat are of these shot objects and that face toward the lens and are notblocked, where the maximum area can be displayed in the image, that is,a maximum area covered by an image visual field. This maximum area maynot be a plane.

The wide-area visual area refers to a shot area that is determined byemulating a relatively large observation range of a human eye, and thepreset wide-area visual area may be a relatively large shot area that isdetermined by a photographer in advance.

To obtain a composite wide-area image of a preset wide-area visual area,the present disclosure creatively considers to shoot a shot object thatenters the preset wide-area visual area, to obtain a global image, shootdifferent portions of a shooting scenario that enter the presetwide-area visual area, to obtain at least two partial images, and usethe global image as a reference image to splice the partial images, toobtain a composite wide-area image. The global image needs to cover atleast an overlap portion of view ranges of the several partial images.Certainly, the global image may also cover all view ranges of theseveral partial images in the preset wide-area visual area. Further, toensure that a view range of the spliced composite wide-area image coversa visual field range of the preset wide-area visual area determined bythe photographer, a sum of the view ranges covered by the at least twopartial images needs to be greater than or equal to a view range coveredby the global image.

It should be noted that, capturing a global image in a preset wide-areavisual area may be performed by a shooting device that has a wide-anglelens or an ultra-wide-angle lens. Capturing at least two partial imagesin the preset wide-area visual area may be performed by at least twoshooting devices, where each shooting device has a standard lens or ahigh-definition lens. A definition of the composite wide-area image isinevitably equal to or less than a definition of the partial images.Therefore, the photographer may determine, according to an expecteddefinition, a shooting device for capturing the partial images.Optionally, the shooting device may be a camera or a video camera.

In this embodiment of the present disclosure, a camera or a video camerathat has a standard lens is briefly referred to as a standard camera inthe following, and a camera or a video camera that has a wide-angle lensis briefly referred to as a wide-angle camera in the following. Further,for capturing at least two partial images in the preset wide-area visualarea, view ranges of neighboring standard cameras of multiple standardcameras may be set to partially overlap, to ensure that spliceprocessing may be performed on partial images captured by a standardlens or a high-definition lens, to obtain the composite wide-area imageof the preset wide-area visual area.

Further, the definition of the partial images may be greater than orequal to a definition of the global image in the preset wide-area visualarea.

Further, capturing a global image in a preset wide-area visual area, andcapturing at least two partial images in the preset wide-area visualarea may include enabling viewpoints for the wide-angle camera and thestandard camera to capture images to be as near as possible.

For example, a wide-angle camera is located at a front and centerposition of a to-be-captured wide-area visual area, where the visualarea covers a global preset wide-area visual area, and at a positionthat is as near as possible and that is in a horizontal direction or avertical direction of the wide-angle camera, at least two standardcameras are distributed to capture partial images.

Further, capturing a global image in a preset wide-area visual area, andcapturing at least two partial images in the preset wide-area visualarea may further include enabling the at least two standard cameras tobe symmetrically distributed around the wide-angle camera.

For example, capturing at least two partial images in the presetwide-area visual area may be capturing four partial images, wherecontent of the partial images is separately the same as content ofimages that are captured from the top left corner, the top right corner,the bottom left corner, and the bottom right corner of the global image,a viewpoint of a standard camera for capturing the partial images is asnear as possible to a viewpoint of the wide-angle camera, and viewranges of neighboring partial images of the partial images overlap.

Step 102: Determine, based on same shot objects that are in the partialimages and that are in the global image, positions that are of edges ofthe partial images, and perform splice processing on the at least twopartial images according to the positions that are of the edges of thepartial images and that are in the global image, to obtain a compositewide-area image of the wide-area visual area.

Generally, a definition of a global image captured by a wide-anglecamera that has a wide-angle lens or an ultra-wide-angle lens isrelatively low, and to obtain a composite wide-area image that has arelatively high definition, splice processing needs to be performed onthe at least two partial images. In a process of splice processing,shooting positions and/or shooting angles for the at least two partialimages are different during the capturing. Therefore, image information,such as a shape or a size, of a same shot object is different indifferent cameras, and the at least two partial images generally cannotbe directly spliced because neighboring edges of the at least twopartial images have an overlap area. In this case, positions that are ofedges of the partial images and that are in the global image may bedetermined according to spatial structure information of shot objectsthat is provided by the global image, that is, according to same shotobjects (which may also be referred to as corresponding shot objects,which essentially refer to same objects that are shot in the partialimages and the global image) in the partial images and the global image,and the splice processing may be performed on the at least two partialimages according to the positions that are of the edges of the partialimages and that are in the global image, to obtain a composite wide-areaimage that has a relatively high definition. The image information ofthe same shot object includes but is not limited to information such asa position, a shape, a size, a color, and brightness.

Determining, in the global image, positions that are of edges of thepartial images, based on same shot objects that are in the partialimages and also in the global image, and performing splice processing onthe at least two partial images according to the positions that are ofthe edges of the partial images and that are in the global image, toobtain a composite wide-area image may further include determining,according to color attributes of pixels in the partial images and colorattributes of pixels in the global image, the same shot objects that arein the partial images and that are in the global image, determining,according to the same shot objects that are in the partial images andthat are in the global image, the positions that are of the edges of thepartial images and that are in the global image, determining an overlaparea of the at least two partial images according to the positions thatare of the edges of the partial images and that are in the global image,where the overlap area is an overlap area of the shot objects in the atleast two partial images, and determining a splice joint between the atleast two partial images according to the overlap area of the at leasttwo partial images such that an image in the overlap area of the atleast two partial images evenly transits, and performing spliceprocessing on the at least two partial images according to thedetermined splice joint.

By means of a wide-area image acquiring method provided in thisembodiment, a global image in a preset wide-area visual area and atleast two partial images in the preset wide-area visual area arecaptured, where the global image covers at least an overlap portion ofview ranges of the partial images in the preset wide-area visual area,and a sum of the view ranges covered by the at least two partial imagesis greater than or equal to a view range covered by the global image,positions that are of edges of the partial images and that are in theglobal image are determined based on same shot objects that are in thepartial images and that are in the global image, and then spliceprocessing is performed on the at least two partial images according tothe positions that are of the edges of the partial images and that arein the global image, to obtain a composite wide-area image whosedefinition is the same as that of the partial images, which increases animage precision in the wide-area image acquiring method.

FIG. 2A is a flowchart of another optional implementation manner of thewide-area image acquiring method shown in FIG. 1. To enable positionsthat are of edges of the partial images and that are in the global imageto be more accurately acquired, and an expected resolution of acomposite wide-area image to be the same as a resolution of the partialimages, as shown in FIG. 2A, before the step 102 of determining, in theglobal image, positions that are of edges of the partial images, basedon same shot objects that are in the partial images and also in theglobal image, this embodiment further include the following steps.

Step 2025: Adjust a pixel quantity of the global image such that anadjusted pixel quantity of same shot objects in the global image is thesame as a pixel quantity of the same shot objects in the partial images.

It should be noted that, a view range of a single partial image issmaller than that of the global image. Therefore, a pixel quantity of asame shot object in the partial image is generally greater than a pixelquantity of the same shot object in the global image. For the purposethat the global image can be used as a reference image to splice thepartial image, the pixel quantity of the same shot object in the globalimage needs to be the same as the pixel quantity of the same shot objectin the partial image.

For example, if a total pixel quantity of the at least two partialimages=a resolution of a camera for capturing the partial images*animage size of a single partial image*a quantity of the partial images,and a total pixel quantity of the global image=a resolution of a camerafor capturing the global image*a size of the single global image*1, itindicates that a pixel quantity of a same shot object in the globalimage is less than a pixel quantity of the same shot object in thepartial images when the total pixel quantity of the global image is lessthan the total pixel quantity of the at least two partial images, andtherefore, the total pixel quantity of the global image needs to beadjusted, and optionally, the pixel quantity of the global image may beadjusted using a method for adjusting the resolution of the global imageor adjusting both the resolution and the size.

Optionally, adjusting a pixel quantity of the global image furtherincludes separately matching feature points of the at least two partialimages with features points of the global image, performing fitting onmatched feature points, and performing interpolation calculation onfitted feature points, to obtain an adjusted global image, where thematched feature points are feature points whose color attributes ofpixels are the same.

The performing fitting on matched feature points, and performinginterpolation calculation on fitted feature points, to obtain anadjusted global image may further include obtaining an adjustmenttransformation matrix by means of fitting according to a positiontransformation relationship between the matched feature points in thepartial images and the matched feature points in the global image,determining, according to the adjustment transformation matrix,positions that are of all first pixels in the global image and that arein the adjusted global image, and filling, with second pixels, positionsthat are in the adjusted global image and that are other than those ofthe first pixels, to obtain an adjusted image.

The foregoing implementation manner is briefly described using asimplified example, as follows.

If a camera for capturing a partial image and a camera for capturing aglobal image are same cameras and use same setting of shootingparameters, and a quantity of partial images is 4, that is a resolutionof the camera for capturing a partial image=a resolution of the camerafor capturing a global image, and a pixel quantity of a single partialimage=a pixel quantity of a single global image, a total pixel quantityof the global image is less than a total pixel quantity of the at leasttwo partial images.

Then, adjustment processing may be performed on the global image, whichmay be that the global image is stretched by two times separately in alength direction and a width direction, an empty pixel after the stretchis filled with a color of a near pixel. It should be noted that, in theforegoing simplified example, deformation factors for the partial imagesand the global image are not considered, and feature point matching isperformed directly using the stretch method. A person skilled in the artshould understand that implementation manners of the present disclosureshould not be limited thereto.

The pixel quantity of the global image is adjusted such that spliceprocessing such as point-by-point matching and alignment may beperformed, at a same pixel level, between the partial images and theglobal image.

Further, shooting positions and/or shooting angles for the at least twopartial images are different during the capturing, and therefore avisual difference exists between the at least two partial images. Toeliminate this visual difference, before the step 102 of determining, inthe global image, positions that are of edges of the partial images,based on same shot objects that are in the partial images and also inthe global image, the method further includes the following steps.

Step 2027: Separately perform alignment processing between the same shotobjects in the at least two partial images and the same shot objects inthe global image, to eliminate a visual difference between the at leasttwo partial images.

The visual difference between the at least two partial images refers tothat viewing angles of shot objects presented in the at least twopartial images are different because the shooting positions and/orshooting angles for the at least two partial images are different duringthe capturing. This parallax difference is similar to a case in whichimages separately acquired by two human eyes have a slight positionoffset. In other words, an observer discovers that a spatial positionrelationship between content of partial images that are presented by awide-area image that is synthesized by directly splicing the at leasttwo partial images is not coordinated, and relative positions do notconform to spatial positions of actual shot objects. In this embodimentof the present disclosure, the alignment processing is separatelyperformed between the same shot objects in the at least two partialimages and the same shot objects in the global image, which caneliminate the parallax difference between the at least two partialimages.

Optionally, separately performing alignment processing between the sameshot objects in the at least two partial images and the same shotobjects in the global image may be performed before determining anoverlap area of the at least two partial images based on the positionsthat are of the edges of the partial images and that are in the globalimage, where the overlap area is an overlap area of the shot objects inthe at least two partial images, and determining a splice joint betweenthe at least two partial images according to the overlap area of the atleast two partial images in step 102.

Further, FIG. 2B is a detailed flowchart of step 2027 in the methodshown in FIG. 2A. As shown in FIG. 2B, step 2027 of the separatelyperforming alignment processing between the same shot objects in the atleast two partial images and the same shot objects in the global imagefurther includes the following steps.

Step 2027-1: Determine matched feature points that are in the partialimages and that are in the global image, where the matched featurepoints are feature points whose color attributes of pixels are the same,and initially estimate, according to the matched feature points, thesame shot objects that are in the partial images and that are in theglobal image.

Step 2027-2: Revise the initially estimated same shot objects accordingto a distance from a matched feature point in the at least two partialimages to a neighboring pixel of the feature point, and a sum of offsetsbetween all matched feature points in the partial images and all matchedfeature points in the global image using a Markov random fieldalgorithm, where the offset is a sum of a first distance and a seconddistance, where the first distance is an offset distance between amatched feature point in the partial images and a matched feature pointin the global image, and the second distance is an offset distancebetween a neighboring pixel of a matched feature point in the partialimages and a neighboring pixel of a matched feature point in the globalimage.

Step 2027-3: Perform deformation processing on the partial imagesaccording to the revised same shot objects that are in the partialimages and that are in the global image such that the same shot objectsin the at least two partial images are separately aligned with the sameshot objects in the global image.

Determining matched feature points that are in the partial images andthat are in the global image refers to establishing a feature pointmatching correspondence between the same shot objects that are in thepartial images and that are in the global image. To select the featurepoints is to select some points on a boundary of a target objectaccording to color variation. Initially estimating, according to thefeature points, the same shot objects that are in the partial images andthat are in the global image refers to speculating a point-by-pointmatching relationship between another point in the partial images andthe same shot objects in the global image according to a quantity offeature points whose matching relationship is determined.

Optionally, an optional implementation manner for obtaining the initialestimation in step 2027-1 further includes predicting points that are inthe global image and that match points of positions most neighboring tothe feature points in the partial images, and successively predictingpoints that are in the partial images and that match points of positionsmost neighboring to the predicted points in the global image, to obtainthe pixel-by-pixel initial estimation of the same shot objects of theentire image.

There is another optional implementation manner for obtaining theinitial estimation in step 2027-1. For details, refer to the followingdescriptions.

Optionally, the wide-area image acquiring method shown in FIG. 1 furtherincludes a third optional implementation manner.

As shown in FIG. 2A, before determining, in the global image, positionsthat are of edges of the partial images, based on same shot objects thatare in the partial images and also in the global image, the method mayfurther include the following steps.

Step 2026-01: Capture a first calibration image corresponding to thepartial images and a second calibration image corresponding to theglobal image, where a visual area of the first calibration imageincludes at least one calibration board that is on a same plane, and avisual area of the second calibration image includes the calibrationboard in the visual area of the first calibration image.

Step 2026-02: Enlarge the second calibration image, and performdistortion correction processing on the second calibration imageaccording to a distortion coefficient of the global image, to obtain afirst corrected image of the global image.

Step 2026-03: Calculate a distortion coefficient of the partial imagesaccording to the first calibration image and the first corrected image.

Step 2026-04: Perform distortion correction processing on the partialimages according to the distortion coefficient of the partial images.

The distortion correction processing is performed on the partial imagesto eliminate distortions that are of the partial images and that are ina horizontal direction and a vertical direction. Distortion correctionis performed on the subsequently captured partial images according tothe distortion coefficient of the partial images, which may obtain abetter splice effect. Similarly, the distortion correction processing isperformed on the at least two partial images, which may obtain a bettersplice effect. In addition, the at least two partial images on which thedistortion correction has been performed can coincide with an area of acalibration board in an image obtained after enlargement and distortioncorrection are performed on the global image.

Optionally, the distortion coefficient of the global image may bedetermined in advance using the following steps, including capturing athird calibration image corresponding to the global image in the presetwide-area visual area in advance, where the preset wide-area visual areaincludes a calibration board, enlarging the third calibration imagecorresponding to the global image in the preset wide-area visual area,and calculating the distortion coefficient of the global image accordingto the calibration image corresponding to the global image and theenlarged third calibration image.

Positions of a ruler on the calibration board in the third calibrationimages corresponding to the global image before and after theenlargement are compared such that the distortion coefficient of theglobal image can be obtained.

Optionally, the distortion correction processing may be performed on theglobal image according to the distortion coefficient of the globalimage.

A calculation method for the distortion coefficient of the global imageis similar to a calculation method for the distortion coefficient of thepartial images. Details are not described herein.

Optionally, the wide-area image acquiring method shown in FIG. 1 furtherincludes a fourth optional implementation manner. Before performingsplice processing on the at least two partial images according to thedetermined splice joint in step 102 and after step 2027-2, the methodmay include performing filtering and restriction processing on thecorrected partial images.

The filtering and restriction processing is used to suppress noise inair flow field data obtained using the Markov random field algorithm.

Optionally, to improve image quality and a splice effect, the wide-areaimage acquiring method shown in FIG. 1 further includes a fifth optionalimplementation manner, and before step 102, includes the followingsteps.

Step 2024: Perform pre-enhancement processing on the global image andthe at least two partial images.

Optionally, one or more types of processing such as image denoising,color balancing, and brightness balancing are performed on the globalimage and the at least two partial images.

Optionally, during the brightness balancing processing, an illuminationparameter of the partial images may be recorded, to performpost-enhancement processing on the spliced composite wide-area image.Step 2024 may be performed before steps 2025 to 2027, or may beperformed after steps 2025 to 2027.

Optionally, to improve image quality and a splice effect of thecomposite wide-area image, the wide-area image acquiring method shown inFIG. 1 further includes a sixth optional implementation manner, andafter determining, in the global image, positions that are of edges ofthe partial images, based on same shot objects that are in the partialimages and also in the global image, and performing splice processing onthe at least two partial images according to the positions that are ofthe edges of the partial images and that are in the global image in step102, the method includes the following step.

Step 203: Perform post-enhancement processing on the composite wide-areaimage of the preset wide-area visual area.

Optionally, the performing post-enhancement processing on the compositewide-area image may include performing cutting processing, illuminationconsistency processing, detail enhancement, and contrast enhancement onthe composite wide-area image. The cutting processing can cut anirregular image boundary, and the illumination consistency processingmay be performed according to the illumination parameter recorded in thepre-enhancement processing.

In this embodiment, a global image in a preset wide-area visual area andat least two partial images in the preset wide-area visual area arecaptured, where the global image covers at least an overlap portion ofview ranges of the partial images in the preset wide-area visual area,and a sum of the view ranges covered by the at least two partial imagesis greater than or equal to a view range covered by the global image,positions that are of edges of the partial images and that are in theglobal image are determined based on same shot objects that are in thepartial images and that are in the global image, and then spliceprocessing is performed on the at least two partial images according tothe positions that are of the edges of the partial images and that arein the global image, to obtain a composite wide-area image of thewide-area visual area, which increases an image definition in thewide-area image acquiring method.

Optionally, the initially estimating, according to the feature points,the same shot objects that are in the partial images and that are in theglobal image in step 2027-1 in this embodiment of the present disclosuremay include another optional implementation manner, including performingthe following operations on each first matched feature point that is inthe partial images and that is in the global image. Using projectioncoordinates that are of the first feature point and that are in thepartial images as a first estimation point, and acquiring an epipolarline that is of the first estimation point and that is in the globalimage, searching the epipolar line of the first estimation point for asecond feature point that matches the first feature point and that is inthe global image, and using a set of the first feature point and a setof the second feature point as the same shot objects that are in thepartial images and that are in the global image.

In searching the epipolar line of the first estimation point for asecond feature point, a geometry principle of the epipolar line is used.In short, in images that are of a same shot object and that are shot bydifferent cameras, if a position of a shooting point of the shot objectis determined in an image, that is, an estimation point, a correspondingpoint in another image must be on an epipolar line of the other imagecorresponding to the estimation point. In other words, the epipolar lineof the point is searched for a point that is in the global image andthat matches a point in the partial image, which may increase a speed ofinitially estimating a matching relationship between image content inthe partial images and image content in the global image. This methodfor eliminating a visual difference between images involves a relativelysmall calculation amount, which not only increases an image synthesisspeed, but also can reduce a performance requirement for an imagesynthesis processor.

Further, performing deformation processing on the partial imagesaccording to the revised same shot objects that are in the partialimages and that are in the global image such that the same shot objectsin the at least two partial images are separately aligned with the sameshot objects in the global image in step 2027-3 may include anotheroptional implementation manner, including separately assigning colorvalues of points in the partial images to a point that is in the partialimages and whose coordinates are the same as those of offset points ofthe points, to obtain a second corrected image corresponding to thepartial images.

Further, an epipolar line that is of the points in the partial image andthat is in the global image may be obtained in advance using thefollowing steps, including determining a first plane, that is, animaging plane of the partial images according to an optical centerposition, a focal length, a shooting direction, and a shooting wideangle of the standard camera for capturing the partial images,determining a second plane, that is, an imaging plane of the globalimage according to an optical center position, a focal length, ashooting direction, and a shooting wide angle of the wide-angle camerafor capturing the global image, selecting a point on the first plane,and marking the point as a first calibration point, determining a thirdplane according to the optical center position of the standard camera,the optical center position of the wide-angle camera, and a position ofthe first calibration point in three-dimensional space, uniquelydetermining, according to the third plane and the second plane, astraight line between the two intersecting planes, where the straightline is an epipolar line that is of the first calibration point and thatis on the second plane, and successively acquiring epipolar lines forpoints in a calibration area in the at least two partial images.

In a case in which the optical center position, the focal length, theshooting direction of the standard camera are determined, the firstcalibration point selected on the first plane may be a position ofimaging that is of a point and that is on the imaging plane of thepartial images, where the point has any depth of field and is on a raythat starts from the optical center position of the standard camera andpasses through the first calibration point. According to the geometryprinciple of the epipolar line, all possible positions of imaging thatare on the global image and that are of the point that has any depth offield and that is on the ray are the epipolar line of the firstcalibration point. In other words, according to a position of a point inthe partial images and an epipolar line that is of the point and that isin the global image, the epipolar line in the global image may besearched for a matching point that is of the point in the partial imagesand that is in the global image, which reduces a search range, andsimplifies a work amount of splice processing.

Optionally, feature points and matching points in the partial images andthe global image may be separately acquired, to determine the firstplane and the second plane. Optionally, feature points and matchingpoints in the partial images and the first corrected image of the globalimage may be separately acquired, to determine the first plane and thesecond plane.

Optionally, a quantity of points and selection of positions of thepoints in the calibration area may be determined according to adefinition need. For example, equidistant points in the calibration areamay be selected to acquire an epipolar line.

Optionally, the epipolar line may be approximately in the horizontaldirection, that is, only a deformation degree of image content in thehorizontal direction is considered, to simplify an algorithmimplementation difficulty.

In this embodiment of the present disclosure, the step of acquiring anepipolar line from several feature points in the partial images tomapped points in the global image in advance according to the geometryprinciple of the epipolar line, to obtain initial estimation of thematching relationship between the image content in the partial imagesand the image content in the global image can eliminate the visualdifference between the partial images.

Optionally, if the capturing a global image in a preset wide-area visualarea is capturing a 360-degree wide-angle image, the capturing at leasttwo partial images in the preset wide-area visual area may be capturingmore than two partial images, to ensure image quality of the partialimages used for splice processing. For example, a capturing viewpoint ofthe global image is used as a center, and seven standard cameras aredistributed at near points whose distances to the viewpoint are equal,to capture partial images. For another example, a capturing viewpoint ofthe global image is used as a center, and three standard cameras areseparately distributed in four directions around the viewpoint, tocapture partial images, where a standard lens in each direction isperpendicular or parallel to a standard lens in another direction.

In this embodiment of the present disclosure, a global image and atleast two partial images in a preset wide-area visual area are acquired,and a series of splice processing such as revision, estimation, andalignment that are described above is performed on the at least twopartial images using the global image as reference, which can obtain acomposite wide-area image in which a visual difference is eliminated.

FIG. 3 is still another optional implementation manner of the wide-areaimage acquiring method shown in FIG. 1. When the wide-area imageacquiring method provided in this embodiment of the present disclosureis applied to acquiring of a wide-area video, in another optionalimplementation manner further included in the wide-area image acquiringmethod shown in FIG. 1.

Step 101 of the capturing a global image in a preset wide-area visualarea, and capturing at least two partial images in the preset wide-areavisual area, where the global image covers at least an overlap portionof view ranges of the partial images in the preset wide-area visualarea, a sum of the view ranges covered by the at least two partialimages is greater than or equal to a view range covered by the globalimage further includes the following step.

Step 301: Capture a global image that is in each frame and that is inthe preset wide-area visual area and at least two partial images thatare in each frame and that are in the preset wide-area visual area,where for each frame, the global image in the frame covers at least anoverlap portion of view ranges of the partial images in the frame, and asum of the view ranges covered by the at least two partial images in theframe is greater than or equal to a view range covered by the globalimage in the frame.

For an implementation manner of step 301, refer to the description instep 101 in the previous embodiment. Details are not described herein.

Step 102 of determining, in the global image, positions that are ofedges of the partial images, based on same shot objects that are in thepartial images and also in the global image, and performing spliceprocessing on the at least two partial images according to the positionsthat are of the edges of the partial images and that are in the globalimage, to obtain a composite wide-area image of the wide-area visualarea further includes the following step.

Step 302: For each frame, determine, based on a same shot object that isin each of the partial images in the frame and that is in the globalimage in the frame, a position that is of an edge of each partial imagein the frame and that is in the global image in the frame, and performsplice processing on the at least two partial images in the frame, toobtain a composite wide-area image that is in the frame and that is ofthe wide-area visual area.

A process for a video camera to capture a video is equivalent to aprocess of capturing consecutive images, that is, the wide-area videoincludes global images with consecutive frames. In other words, theacquiring of the wide-area video can be translated into acquiring of theglobal images with consecutive frames in the wide-area video. Each frameis a synchronous capturing cycle of the partial images and the globalimage. In each cycle, a corresponding quantity of partial images and theglobal image are captured. A step of acquiring each frame of wide-areaimage in the wide-area video is similar to step 102 in the wide-areaimage acquiring method in this embodiment of the present disclosure.Only difference is that, a video camera performs image splice processingusing each frame as the unit. Details are not described herein.

Optionally, before step 302, the method may include temporarily storingthe global image in the preset wide-area visual area in each frame andthe at least two partial images in the preset wide-area visual area ineach frame that are captured in step 301, to ensure that the globalimage in each frame is processed according to a sequence of capturingeach frame.

Using several specific embodiments, the following describes in detailthe technical solutions in the method embodiments shown in FIG. 1 toFIG. 3.

For example, this embodiment of the present disclosure is applied when acomposite wide-area image is acquired. A global image in the presetwide-area visual area and four partial images in the preset wide-areavisual area may be captured using one camera that has a wide-angle lensand four cameras that have standard lenses, to synthesize a wide-areaimage, where an optical center, a shooting direction, and a shootingdistance of the camera that has the wide-angle lens may be determinedaccording to a position of a shot area, as long as the shot area isglobally covered, optical centers of the cameras that have the standardlenses may be placed at a position that is near the optical center ofthe camera that has the wide-angle lens, and shooting ranges areseparately adjusted for the cameras that have the standard lenses, torespectively cover the top left corner, the top right corner, the bottomleft corner, and the bottom right corner of the shot area, and it isensured that a sum of the shooting ranges of the four cameras that havethe standard lenses covers the entire shot area, and shooting ranges ofneighboring cameras that have standard lenses overlap slightly.Similarly, when this embodiment of the present disclosure is applied toacquiring of a wide-area video, a global image in a preset wide-areavisual area in each frame and four partial images in the presetwide-area visual area may be captured using one video camera that has awide-angle lens and four video cameras that have standard lenses, tosynthesize a wide-area image frame by frame, and finally obtain awide-area video. The following provides detailed descriptions.

FIG. 4A and FIG. 4B are a flowchart of Embodiment 2 of a wide-area imageacquiring method according to the present disclosure. FIG. 4C is aflowchart of an optional implementation manner of step S4033 in themethod shown in FIG. 4A and FIG. 4B. FIG. 4D is a flowchart of anotheroptional implementation manner of step S4033 in the method shown in FIG.4A and FIG. 4B. FIG. 5A is a schematic diagram of data processing ofstep S401 and step S402 in the method shown in FIG. 4A and FIG. 4B toFIG. 4D. FIG. 5B is a schematic diagram of data processing of step S4031in the method shown in FIG. 4A and FIG. 4B to FIG. 4D. FIG. 5C is aschematic diagram of data processing of step S4032 in the method shownin FIG. 4A and FIG. 4B to FIG. 4D. FIG. 5D is a schematic diagram ofdata processing of step S4033 in the method shown in FIG. 4A and FIG. 4Bto FIG. 4D. FIG. 5E is a schematic diagram of data processing of stepsS4033-11, S4033-12, and S4033-13 in the method shown in FIG. 4A and FIG.4B to FIG. 4D. FIG. 5F is a schematic diagram of data processing of stepS4038-3 in the method shown in FIG. 4A and FIG. 4B to FIG. 4D. FIG. 5Gis a schematic diagram of data processing of step S4038-4 in the methodshown in FIG. 4A and FIG. 4B to FIG. 4D.

As shown in FIG. 4A and FIG. 4B, the method in this embodiment mayinclude the following steps.

Step S400-1: Acquire a distortion coefficient of the global image inadvance.

Step S400-2: Acquire a distortion coefficient of the at least twopartial images in advance.

The at least two partial images are described using four partial imagesas an example.

Step S401: Capture the global image in a preset wide-area visual area.

Step S402: Capture the at least two partial images in the presetwide-area visual area.

The at least two partial images are described using four partial imagesas an example. Data processing in steps S401 and S402 is shown in FIG.5A, where 1, 2, 3, and 4 are visual areas covered by the partial images,and 0 is a visual area covered by the global image. Correspondingly, A,B, C, and D are the partial images, and E is the global image.

Step S403-0: Perform pre-enhancement processing.

The pre-enhancement processing may be any one or more of imagedenoising, color balancing, or brightness balancing.

Step 102, which is shown in FIG. 1, of the determining, in the globalimage, positions that are of edges of the partial images, based on sameshot objects that are in the partial images and also in the globalimage, and performing splice processing on the at least two partialimages according to the positions that are of the edges of the partialimages and that are in the global image, to obtain a composite wide-areaimage of the wide-area visual area may further include the followingstep.

Step S4031: Adjust a pixel quantity of the global image.

Data processing in step S4031 is shown in FIG. 5B.

Step S4032: Perform distortion correction processing on the global imageaccording to the distortion coefficient of the global image, andseparately perform distortion correction processing on the partialimages according to the distortion coefficient of the at least twopartial images.

Data processing in step S4032 is shown in FIG. 5C.

Step 102, which is shown in FIG. 1, of the separately performingalignment processing between the same shot objects in the at least twopartial images and the same shot objects in the global image, toeliminate a visual difference between the at least two partial imagesmay further include processing in steps S4033, S4033, and S4035.

Step S4033: Determine matched feature points that are in the partialimages and that are in the global image, where the matched featurepoints are feature points whose color attributes of pixels are the same,and initially estimate, according to the feature points, same shotobjects that are in the partial images and that are in the global image.

Data processing in step S4033 is shown in FIG. 5D. According to sparsefeature point matching, the same shot objects in the partial images maybasically coincide with the same shot objects in the global image, whichis equivalent to determining approximate positions that are of thepartial images and that are in the global image.

Optionally, step S4033 may further include the method in steps S4033-01and S4033-02 of FIG. 4C or the method in steps S4033-11, S4033-12, andS4033-13 of FIG. 4D.

Step S4033-01: Predict points that are in the global image and thatmatch points of positions most neighboring to the feature points in thepartial images.

Step S4033-02: Successively predict points that are in the global imageand that match points of most neighboring positions in the partialimages, to obtain pixel-by-pixel initial estimation of the same shotobjects of the entire image.

Step S4033-11: Select, in the global image, a point in an overlap areaof the global image and the partial images, record projectioncoordinates that are of the point and that are in the partial images,mark the point as a first estimation point, and acquire an epipolar linethat is of the first estimation point and that is in the global image.

Step S4033-12: Search the epipolar line of the first estimation pointfor a first matching point, that is, a point that matches the firstestimation point and that is in the global image.

Step S4033-13: Successively search for matching points corresponding toall points in the partial images.

Data processing in steps S4033-11, S4033-12, and S4033-13 is shown inFIG. 5E.

Step S4034: Revise the initially estimated same shot objects accordingto a distance from a matched feature point in the at least two partialimages to a neighboring pixel of the feature point, and a sum of offsetsbetween all matched feature points in the partial images and all matchedfeature points in the global image using a Markov random fieldalgorithm.

The offset is a sum of a first distance and a second distance, where thefirst distance is an offset distance between a matched feature point inthe partial images and a matched feature point in the global image, andthe second distance is an offset distance between a neighboring pixel ofa matched feature point in the partial images and a neighboring pixel ofa matched feature point in the global image.

Step S4035: Perform deformation processing on the partial imagesaccording to the revised same shot objects that are in the partialimages and that are in the global image such that the same shot objectsin the at least two partial images are separately aligned with the sameshot objects in the global image.

Step S4036: Perform filtering and restriction processing on the revisedpartial images.

Step S4037: Fill a blackhole area in the partial images with pixelsaccording to a shot object in the global image.

The blackhole area is a shot object that exists in the global image butcannot be displayed in the partial images due to mutual block byobjects.

Step 102, which is shown in FIG. 1, of determining, in the global image,positions that are of edges of the partial images, based on same shotobjects that are in the partial images and also in the global image, andperforming splice processing on the at least two partial imagesaccording to the positions that are of the edges of the partial imagesand that are in the global image, to obtain a composite wide-area imageof the wide-area visual area may further include processing in stepsS4038-1, S4038-2, S4038-3, and S4038-4.

Step S4038-1: Determine, according to color attributes of pixels in thepartial images and color attributes of pixels in the global image, thesame shot objects that are in the partial images and that are in theglobal image.

Step S4038-2: Determine, according to the same shot objects that are inthe partial images and that are in the global image, positions that areof edges of the partial images and that are in the global image.

Step S4038-3: Determine an overlap area of the at least two partialimages according to the positions that are of the edges of the partialimages and that are in the global image, where the overlap area is anoverlap area of the shot objects in the at least two partial images, anddetermine a splice joint between the at least two partial imagesaccording to the overlap area of the at least two partial images suchthat an image in the overlap area of the at least two partial imagesevenly transits.

Data processing in step S4038-3 is shown in FIG. 5F.

Step S4038-4: Perform splice processing on the at least two partialimages according to the determined splice joint.

Data processing in S4038-4 is shown in FIG. 5G.

Step S403-1: Perform post-enhancement processing.

Performing post-enhancement processing on the composite wide-area imagewhose definition is preset may include performing cutting processing,illumination consistency processing, detail enhancement, and contrastenhancement on the composite wide-area image whose definition is preset.

According to the implementation manner of the method shown in FIG. 1, aperson skilled in the art should understand that, steps S400-1, S400-2,S403-0, S4031 to S4037, and S403-1 in this embodiment are optional stepsin this embodiment of the present disclosure. For an optional scenariofor the foregoing steps, refer to the implementation manner of themethod shown in FIG. 1. Details are not described herein.

FIG. 6 is a flowchart of Embodiment 3 of a wide-area image acquiringmethod according to the present disclosure. FIG. 7 is a schematicdiagram of data processing of step S601 in the method shown in FIG. 6.As shown in FIG. 6, the method in this embodiment may include thefollowing steps.

Step S601: Capture a global image that is in each frame and that is inthe preset wide-area visual area and at least two partial images thatare in each frame and that are in the preset wide-area visual area.

For each frame, the global image in the frame covers at least an overlapportion of view ranges of the partial images in the frame, and a sum ofthe view ranges covered by the at least two partial images in the frameis greater than or equal to a view range covered by the global image inthe frame.

Step S602: For each frame, determine, based on a same shot object thatis in each of the partial images in the frame and that is in the globalimage in the frame, a position that is of an edge of each partial imagein the frame and that is in the global image in the frame, and performsplice processing on the at least two partial images in the frame, toobtain a composite wide-area image that is in the frame and that is ofthe wide-area visual area.

Step S603: Output the composite wide-area image of the wide-area visualarea frame by frame.

Data processing in step S601 is shown in FIG. 7, where P1, P2, P3, P4,and Pn indicate consecutive frames, and in each frame, partial images A,B, C, and D and a global image E are separately captured.

The implementation manners in the method shown in FIG. 1 to FIG. 5 maybe used in other steps in this embodiment of the present disclosure, andthe technical effect of the steps is the same. Details are not describedherein.

FIG. 8A is a schematic structural diagram of Embodiment 1 of a wide-areaimage acquiring apparatus according to the present disclosure. As shownin FIG. 8A, the apparatus 1 in this embodiment may include a capturemodule 11 and a processing module 12.

The capture module 11 is configured to capture a global image in apreset wide-area visual area, and capture at least two partial images inthe preset wide-area visual area, where the global image covers at leastan overlap portion of view ranges of the partial images in the presetwide-area visual area, a sum of the view ranges of the at least twopartial images is greater than or equal to a view range of the globalimage.

The processing module 12 is configured to determine, in the globalimage, positions that are of edges of the partial images, based on sameshot objects that are in the partial images and also in the globalimage, and perform splice processing on the at least two partial images,to obtain a composite wide-area image of the wide-area visual area.

View ranges of neighboring partial images captured by the capture module11 may partially overlap.

The apparatus 1 in this embodiment may be configured to execute thetechnical solutions of the method embodiments shown in FIG. 1 to FIG. 7.The implementation principles and technical effects are similar. Detailsare not described herein.

Optionally, FIG. 8B is an optional schematic structural diagram of aprocessing module 12 in Embodiment 1 shown in FIG. 8A. As shown in FIG.8B, the processing module 12 further includes a same shot objectdetermining unit 121 configured to determine, according to colorattributes of pixels in the partial images and color attributes ofpixels in the global image, the same shot objects that are in thepartial images and that are in the global image, and a splice unit 122configured to determine, according to the same shot objects that are inthe partial images and that are in the global image, the positions thatare of the edges of the partial images and that are in the global image,determine an overlap area of the at least two partial images accordingto the positions that are of the edges of the partial images and thatare in the global image, where the overlap area is an overlap area ofthe shot objects in the at least two partial images, and determine asplice joint between the at least two partial images according to theoverlap area of the at least two partial images such that an image inthe overlap area of the at least two partial images evenly transits, andperform splice processing on the at least two partial images accordingto the determined splice joint.

The apparatus in this embodiment may be configured to execute thetechnical solutions of the method embodiments shown in FIG. 1 to FIG. 7.The implementation principles and technical effects are similar. Detailsare not described herein.

Optionally, FIG. 8C is another optional schematic structural diagram ofa processing module 12 in Embodiment 1 shown in FIG. 8A. As shown inFIG. 8C, the processing module 12 further includes a filling unit 123configured to fill a blackhole area in the partial images with pixelsaccording to a shot object in the global image before the processingmodule 12 determines a splice joint between the at least two partialimages, where the blackhole area is a shot object that exists in theglobal image but cannot be displayed in the partial images due to mutualblock by objects. The apparatus 1 in this embodiment may be configuredto execute the technical solutions of the method embodiments shown inFIG. 1 to FIG. 7. The implementation principles and technical effectsare similar. Details are not described herein.

FIG. 9A is a schematic structural diagram of Embodiment 2 of a wide-areaimage acquiring apparatus according to the present disclosure. As shownin FIG. 9A, on the basis of the apparatus 1 shown in FIG. 8A to FIG. 8C,the apparatus 1 in this embodiment of the present disclosure may furtherinclude a global image adjustment module 13.

A resolution of the partial images may be greater than a resolution ofthe global image, and the global image adjustment module 13 may beconfigured to adjust a pixel quantity of the global image before theprocessing module 12 determines, in the global image, positions that areof edges of the partial images, based on same shot objects that are inthe partial images and also in the global image such that an adjustedpixel quantity of the same shot objects in the global image is the sameas a pixel quantity of the same shot objects in the partial images.

The apparatus in this embodiment may be configured to execute thetechnical solutions of the method embodiments shown in FIG. 1 to FIG. 7.The implementation principles and technical effects are similar. Detailsare not described herein.

Optionally, FIG. 9B is an optional schematic structural diagram of aglobal image adjustment module 13 in Embodiment 2 shown in FIG. 9A. Asshown in FIG. 9B, the global image adjustment module 13 includes afeature point matching unit 131 configured to separately perform featurepoint matching between the at least two partial images and the globalimage, where the matched feature points are feature points whose colorattributes of pixels are the same, a fitting unit 132 configured toperform fitting on the matched feature points, and an interpolationcalculation unit 133 configured to perform interpolation calculation onfitted feature points, to obtain an adjusted global image, where theadjusted pixel quantity of the same shot objects in the global image isthe same as the pixel quantity of the same shot objects in the partialimages.

Optionally, the fitting unit 132 may be further configured to obtain anadjustment transformation matrix by means of fitting according to aposition transformation relationship between the matched feature pointsin the partial images and the matched feature points in the globalimage, and determine, according to the adjustment transformation matrix,positions that are of all first pixels in the global image and that arein the adjusted global image, and correspondingly, the interpolationcalculation unit 133 may be further configured to fill, with secondpixels, positions that are in the adjusted global image and that areother than those of the first pixels, to obtain an adjusted image.

The apparatus in this embodiment may be configured to execute thetechnical solutions of the method embodiments shown in FIG. 1 to FIG. 7.The implementation principles and technical effects are similar. Detailsare not described herein.

FIG. 10A is a schematic structural diagram of Embodiment 3 of awide-area image acquiring apparatus according to the present disclosure.As shown in FIG. 10A, on the basis of the apparatus 1 shown in FIG. 8Ato FIG. 9B, the apparatus 1 in this embodiment of the present disclosuremay further include a parallax adjustment module 14.

The parallax adjustment module 14 is configured to separately performalignment processing between the same shot objects in the at least twopartial images and the same shot objects in the global image, toeliminate a visual difference between the at least two partial imagesbefore the processing module 12 determines, in the global image,positions that are of edges of the partial images, based on same shotobjects that are in the partial images and also in the global image.

It should be noted that, in this embodiment of the present disclosure,the global image adjustment module 13 is not a necessary unit, and maybe selected by a person skilled in the art according to a specificsituation.

The apparatus in this embodiment may be configured to execute thetechnical solutions of the method embodiments shown in FIG. 1 to FIG. 7.The implementation principles and technical effects are similar. Detailsare not described herein.

Optionally, FIG. 10B is an optional schematic structural diagram of aparallax adjustment module 14 in Embodiment 3 shown in FIG. 10A. Asshown in FIG. 10B, the parallax adjustment module 14 includes a shotobject initial estimation unit 141 configured to determine the matchedfeature points that are in the partial images and that are in the globalimage, where the matched feature points are feature points whose colorattributes of pixels are the same, and initially estimate, according tothe matched feature points, the same shot objects that are in thepartial images and that are in the global image, a revision unit 142configured to revise the initially estimated same shot objects accordingto a distance from a matched feature point in the at least two partialimages to a neighboring pixel of the feature point, and a sum of offsetsbetween all matched feature points in the partial images and all matchedfeature points in the global image using a Markov random fieldalgorithm, where the offset is a sum of a first distance and a seconddistance, where the first distance is an offset distance between amatched feature point in the partial images and a matched feature pointin the global image, and the second distance is an offset distancebetween a neighboring pixel of a matched feature point in the partialimages and a neighboring pixel of a matched feature point in the globalimage, and a shot object alignment processing unit 143 configured toperform deformation processing on the partial images according to therevised same shot objects that are in the partial images and that are inthe global image such that the same shot objects in the at least twopartial images are separately aligned with the same shot objects in theglobal image.

The apparatus 1 in this embodiment may be configured to execute thetechnical solutions of the method embodiments shown in FIG. 1 to FIG. 7.The implementation principles and technical effects are similar. Detailsare not described herein.

Optionally, FIG. 10C is another optional schematic structural diagram ofthe parallax adjustment module 14 in Embodiment 3 shown in FIG. 10A. Asshown in FIG. 10C, the parallax adjustment module 14 may further includea same shot object determining unit 144 configured to perform thefollowing operations on each first matched feature point that is in thepartial images and that is in the global image using projectioncoordinates that are of the first feature point and that are in thepartial images as a first estimation point, and acquiring an epipolarline that is of the first estimation point and that is in the globalimage, searching the epipolar line of the first estimation point for asecond feature point that matches the first feature point and that is inthe global image, and using a set of the first feature point and a setof the second feature point as the same shot objects that are in thepartial images and that are in the global image.

The apparatus in this embodiment may be configured to execute thetechnical solutions of the method embodiments shown in FIG. 1 to FIG. 7.The implementation principles and technical effects are similar. Detailsare not described herein.

Optionally, FIG. 10D is still another optional schematic structuraldiagram of the parallax adjustment module 14 in Embodiment 3 shown inFIG. 10A. As shown in FIG. 10D, the parallax adjustment module 14 mayfurther include a partial image correction unit 145 configured tocapture a first calibration image corresponding to the partial imagesand a second calibration image corresponding to the global image beforethe processing module 12 determines, in the global image, positions thatare of edges of the partial images, based on same shot objects that arein the partial images and also in the global image, where a visual areaof the first calibration image includes at least one calibration boardthat is on a same plane, and a visual area of the second calibrationimage includes the calibration board in the visual area of the firstcalibration image, enlarge the second calibration image, and performdistortion correction processing on the second calibration imageaccording to a distortion coefficient of the global image, to obtain afirst corrected image of the global image, calculate a distortioncoefficient of the partial images according to the first calibrationimage and the first corrected image, and perform distortion correctionprocessing on the partial images according to the distortion coefficientof the partial images.

The apparatus in this embodiment may be configured to execute thetechnical solutions of the method embodiments shown in FIG. 1 to FIG. 7.The implementation principles and technical effects are similar. Detailsare not described herein.

Persons of ordinary skill in the art may understand that all or a partof the steps of the method embodiments may be implemented by a programinstructing relevant hardware. The program may be stored in a computerreadable storage medium. The steps of the method embodiments areperformed when the program runs. The foregoing storage medium includesany medium that can store program code, such as a read-only memory(ROM), a random-access memory (RAM), a magnetic disc, or an opticaldisc.

Finally, it should be noted that the foregoing embodiments are merelyintended for describing the technical solutions of the presentdisclosure other than limiting the present disclosure. Although thepresent disclosure is described in detail with reference to theforegoing embodiments, persons of ordinary skill in the art shouldunderstand that they may still make modifications to the technicalsolutions described in the foregoing embodiments or make equivalentreplacements to some technical features thereof, without departing fromthe scope of the technical solutions of the embodiments of the presentdisclosure.

What is claimed is:
 1. A wide-area image acquiring method, comprising:capturing a global image in a preset wide-area visual area; capturing atleast two partial images in the preset wide-area visual area, whereinthe global image covers at least an overlap portion of view ranges ofthe partial images in the preset wide-area visual area, wherein a sum ofthe view ranges covered by the at least two partial images is greaterthan or equal to a view range covered by the global image, and whereinthe view range refers to a maximum area covered by an image visualfield; determining, in the global image, positions of edges of thepartial images, based on same shot objects that are in the partialimages and also in the global image; and performing splice processing onthe at least two partial images according to the determined positions ofthe edges, to obtain a composite wide-area image of the wide-area visualarea.
 2. The method according to claim 1, wherein a resolution of thepartial images is greater than a resolution of the global image, andwherein before determining, in the global image, the positions that areof edges of the partial images, based on the same shot objects that arein the partial images and also in the global image, the method furthercomprises adjusting a pixel quantity of the global image such that anadjusted pixel quantity of the same shot objects in the global image isthe same as a pixel quantity of the same shot objects in the partialimages.
 3. The method according to claim 2, wherein adjusting the pixelquantity of the global image further comprises: separately matchingfeature points of the at least two partial images with features pointsof the global image; performing fitting on matched feature points,wherein the matched feature points are feature points whose colorattributes of pixels are the same; and performing interpolationcalculation on fitted feature points, to obtain an adjusted globalimage.
 4. The method according to claim 3, wherein performing fitting onmatched feature points, and performing interpolation calculation onfitted feature points, to obtain the adjusted global image furthercomprises: obtaining an adjustment transformation matrix by means offitting according to a position transformation relationship between thematched feature points in the partial images and the matched featurepoints in the global image; determining, according to the adjustmenttransformation matrix, positions that are of all first pixels in theglobal image and that are in the adjusted global image; and filling,with second pixels, positions that are in the adjusted global image andthat are other than those of the first pixels, to obtain an adjustedimage.
 5. The method according to claim 1, wherein before determining,in the global image, the positions that are of edges of the partialimages, based on the same shot objects that are in the partial imagesand also in the global image, the method further comprises separatelyperforming alignment processing between the same shot objects in the atleast two partial images and the same shot objects in the global image,to eliminate a visual difference between the at least two partialimages.
 6. The method according to claim 5, wherein separatelyperforming the alignment processing between the same shot objects in theat least two partial images and the same shot objects in the globalimage further comprises: determining matching feature points that are inthe partial images and that are in the global image, wherein the matchedfeature points are feature points whose color attributes of pixels arethe same; initially estimating, according to the matched feature points,the same shot objects that are in the partial images and that are in theglobal image; revising the initially estimated same shot objectsaccording to a distance from a matched feature point in the at least twopartial images to a neighboring pixel of the feature point, and a sum ofoffsets between all matched feature points in the partial images and allmatched feature points in the global image using a Markov random fieldalgorithm, wherein the offset is a sum of a first distance and a seconddistance, wherein the first distance is an offset distance between amatched feature point in the partial images and a matched feature pointin the global image, and wherein the second distance is an offsetdistance between a neighboring pixel of the matched feature point in thepartial images and a neighboring pixel of the matched feature point inthe global image; and performing deformation processing on the partialimages according to the revised same shot objects that are in thepartial images and that are in the global image such that the same shotobjects in the at least two partial images are separately aligned withthe same shot objects in the global image.
 7. The method according toclaim 6, wherein determining the matched feature points that are in thepartial images and that are in the global image, and initiallyestimating the same shot objects that are in the partial images and thatare in the global image further comprises: performing the followingoperations on each first matched feature point that is in the partialimages and that is in the global image: setting projection coordinatesthat are of the first feature point and that are in the partial imagesas a first estimation point; acquiring an epipolar line that is of thefirst estimation point and that is in the global image; and searchingthe epipolar line of the first estimation point for a second featurepoint that matches the first feature point and that is in the globalimage; and setting a set of the first feature point and a set of thesecond feature point as the same shot objects that are in the partialimages and that are in the global image.
 8. The method according toclaim 1, wherein before determining, in the global image, the positionsthat are of edges of the partial images, based on the same shot objectsthat are in the partial images and also in the global image, the methodfurther comprises: capturing a first calibration image corresponding tothe partial images and a second calibration image corresponding to theglobal image, wherein a visual area of the first calibration imagecomprises at least one calibration board that is on a same plane, andwherein a visual area of the second calibration image comprises thecalibration board in the visual area of the first calibration image;enlarging the second calibration image; performing distortion correctionprocessing on the second calibration image according to a distortioncoefficient of the global image, to obtain a first corrected image ofthe global image; calculating a distortion coefficient of the partialimages according to the first calibration image and the first correctedimage of the global image; and performing the distortion correctionprocessing on the partial images according to the distortion coefficientof the partial images.
 9. The method according to claim 1, whereindetermining, in the global image, the positions that are of edges of thepartial images, based on the same shot objects that are in the partialimages and also in the global image, and performing splice processing onthe at least two partial images to obtain the composite wide-area imageof the wide-area visual area further comprises: determining, accordingto color attributes of pixels in the partial images and color attributesof pixels in the global image, the same shot objects that are in thepartial images and that are in the global image; determining, accordingto the same shot objects that are in the partial images and that are inthe global image, the positions that are of the edges of the partialimages and that are in the global image; determining an overlap area ofthe at least two partial images according to the positions that are ofthe edges of the partial images and that are in the global image,wherein the overlap area is an overlap area of the shot objects in theat least two partial images; determining a splice joint between the atleast two partial images according to the overlap area of the at leasttwo partial images such that an image in the overlap area of the atleast two partial images evenly transits; and performing the spliceprocessing on the at least two partial images according to thedetermined splice joint.
 10. The method according to claim 9, whereinbefore determining the splice joint between the at least two partialimages, the method further comprises filling a blackhole area in thepartial images with pixels according to a shot object in the globalimage, wherein the blackhole area is a shot object that exists in theglobal image but cannot be displayed in the partial images due to mutualblock by objects.
 11. The method according to claim 1, wherein viewranges of captured neighboring partial images partially overlap.
 12. Themethod according to claim 1, wherein the global image is a dynamicimage, wherein the partial images are dynamic images, wherein capturingthe global image in the preset wide-area visual area, and capturing theat least two partial images in the preset wide-area visual area, furthercomprises capturing a global image that is in each frame and that is inthe preset wide-area visual area and at least two partial images thatare in each frame and that are in the preset wide-area visual area,wherein for each frame, the global image in the frame covers at least anoverlap portion of view ranges of the partial images in the frame,wherein a sum of the view ranges covered by the at least two partialimages in the frame is greater than or equal to a view range covered bythe global image in the frame, and wherein determining, in the globalimage, the positions that are of edges of the partial images, based onthe same shot objects that are in the partial images and also in theglobal image, and performing the splice processing on the at least twopartial images to obtain the composite wide-area image of the wide-areavisual area further comprises: determining, based on a same shot objectthat is in each of the partial images in the frame and that is in theglobal image in the frame, a position that is of an edge of each partialimage in the frame and that is in the global image in the frame for eachframe; and performing the splice processing on the at least two partialimages in the frame according to the position that is of the edge ofeach partial image in the frame and that is in the global image in theframe, to obtain the composite wide-area image that is in the frame andthat is of the wide-area visual area.
 13. A wide-area image acquiringapparatus, comprising: a memory; and a processor coupled to the memoryand configured to: capture a global image in a preset wide-area visualarea; capture at least two partial images in the preset wide-area visualarea, wherein the global image covers at least an overlap portion ofview ranges of the partial images in the preset wide-area visual area,wherein a sum of the view ranges covered by the at least two partialimages is greater than or equal to a view range covered by the globalimage, and wherein the view range refers to a maximum area covered by animage visual field; determine, in the global image, positions that areof edges of the partial images, based on same shot objects that are inthe partial images and also in the global image; and perform spliceprocessing on the at least two partial images according to thedetermined positions of the edges, to obtain a composite wide-area imageof the wide-area visual area.
 14. The apparatus according to claim 13,wherein a resolution of the partial images is greater than a resolutionof the global image, and wherein before determining, in the globalimage, the positions that are of edges of the partial images, based onthe same shot objects that are in the partial images and also in theglobal image, the processor is further configured to adjust a pixelquantity of the global image such that an adjusted pixel quantity of thesame shot objects in the global image is the same as a pixel quantity ofthe same shot objects in the partial images.
 15. The apparatus accordingto claim 14, wherein the processor is further configured to: separatelyperform feature point matching between the at least two partial imagesand the global image, wherein the matched feature points are featurepoints whose color attributes of pixels are the same; perform fitting onthe matched feature points; and perform interpolation calculation onfitted feature points, to obtain an adjusted global image.
 16. Theapparatus according to claim 15, wherein the processor is furtherconfigured to: obtain an adjustment transformation matrix by means offitting according to a position transformation relationship between thematched feature points in the partial images and the matched featurepoints in the global image; determine, according to the adjustmenttransformation matrix, positions that are of all first pixels in theglobal image and that are in the adjusted global image; and fill, withsecond pixels, positions that are in the adjusted global image and thatare other than those of the first pixels, to obtain an adjusted image.17. The apparatus according to claim 13, wherein before determining, inthe global image, the positions that are of edges of the partial images,based on the same shot objects that are in the partial images and alsoin the global image, the processor is further configured to separatelyperform alignment processing between the same shot objects in the atleast two partial images and the same shot objects in the global image,to eliminate a visual difference between the at least two partialimages.
 18. The apparatus according to claim 17, wherein the processoris further configured to: determine matching feature points that are inthe partial images and that are in the global image, wherein the matchedfeature points are feature points whose color attributes of pixels arethe same; initially estimate, according to the matched feature points,the same shot objects that are in the partial images and that are in theglobal image; revise the initially estimated same shot objects accordingto a distance from a matched feature point in the at least two partialimages to a neighboring pixel of the feature point, and a sum of offsetsbetween all matched feature points in the partial images and all matchedfeature points in the global image using a Markov random fieldalgorithm, wherein the offset is a sum of a first distance and a seconddistance, wherein the first distance is an offset distance between amatched feature point in the partial images and a matched feature pointin the global image, and wherein the second distance is an offsetdistance between a neighboring pixel of the matched feature point in thepartial images and a neighboring pixel of the matched feature point inthe global image; and perform deformation processing on the partialimages according to the revised same shot objects that are in thepartial images and that are in the global image such that the same shotobjects in the at least two partial images are separately aligned withthe same shot objects in the global image.
 19. The apparatus accordingto claim 18, wherein the processor is further configured to perform thefollowing operations on each first matched feature point that is in thepartial images and that is in the global image: set projectioncoordinates that are of the first feature point and that are in thepartial images as a first estimation point; acquire an epipolar linethat is of the first estimation point and that is in the global image;search the epipolar line of the first estimation point for a secondfeature point that matches the first feature point and that is in theglobal image; and set a set of the first feature point and a set of thesecond feature point as the same shot objects that are in the partialimages and that are in the global image.
 20. The apparatus according toclaim 17, wherein before determining, in the global image, the positionsthat are of edges of the partial images, based on the same shot objectsthat are in the partial images and also in the global image, theprocessor is further configured to: capture a first calibration imagecorresponding to the partial images and a second calibration imagecorresponding to the global image, wherein a visual area of the firstcalibration image comprises at least one calibration board that is on asame plane, and when a visual area of the second calibration imagecomprises the calibration board in the visual area of the firstcalibration image; enlarge the second calibration image; performdistortion correction processing on the second calibration imageaccording to a distortion coefficient of the global image, to obtain afirst corrected image of the global image; calculate a distortioncoefficient of the partial images according to the first calibrationimage and the first corrected image of the global image; and perform thedistortion correction processing on the partial images according to thedistortion coefficient of the partial images.
 21. The apparatusaccording to claim 13, wherein the processor is further configured to:determine, according to color attributes of pixels in the partial imagesand color attributes of pixels in the global image, the same shotobjects that are in the partial images and that are in the global image;and determine, according to the same shot objects that are in thepartial images and that are in the global image, the positions that areof the edges of the partial images and that are in the global image;determine an overlap area of the at least two partial images accordingto the positions that are of the edges of the partial images and thatare in the global image, wherein the overlap area is an overlap area ofthe shot objects in the at least two partial images; determine a splicejoint between the at least two partial images according to the overlaparea of the at least two partial images such that an image in theoverlap area of the at least two partial images evenly transits; andperform the splice processing on the at least two partial imagesaccording to the determined splice joint.
 22. The apparatus according toclaim 21, wherein before determining the splice joint between the atleast two partial images, the processor is further configured to fill ablackhole area in the partial images with pixels according to a shotobject in the global image, wherein the blackhole area is a shot objectthat exists in the global image but cannot be displayed in the partialimages due to mutual block by objects.
 23. The apparatus according toclaim 13, wherein view ranges of neighboring partial images partiallyoverlap.